code: def _download_extract_wavs(root: str):
      for archive in ["dev", "test"]:
          archive_name = _ARCHIVE_CONFIGS[archive]["archive_name"]
          archive_path = os.path.join(root, archive_name)
          # The zip file of dev data is splited to 4 chunks.
          # Download and combine them into one file before extraction.
          if archive == "dev":
              urls = _ARCHIVE_CONFIGS[archive]["urls"]
              checksums = _ARCHIVE_CONFIGS[archive]["checksums"]
              with open(archive_path, "wb") as f:
                  for url, checksum in zip(urls, checksums):
                      file_path = os.path.join(
                          root, os.path.basename(url)
                      )
                      download_url_to_file(
                          url, file_path, hash_prefix=checksum
                      )
                      with open(file_path, "rb") as f_split:
                          f.write(f_split.read())
          else:
              url = _ARCHIVE_CONFIGS[archive]["url"]
              checksum = _ARCHIVE_CONFIGS[archive]["checksum"]
              download_url_to_file(
                  url, archive_path, hash_prefix=checksum
              )
          _extract_zip(archive_path)
  
imports: import os
  from pathlib import Path
  from typing import List, Tuple, Union
  from torch import Tensor
  from torch.utils.data import Dataset
  from torchaudio._internal import download_url_to_file
  from torchaudio.datasets.utils import _extract_zip, _load_waveform
label_desc: Use image node_id 1 for calling a global function with example usage: _download_extract_wavs(root) without return types